A new approach to Health Benefits Package design: an application of the Thanzi La Onse model in Malawi.

An efficient allocation of limited resources in low-income settings offers the opportunity to improve population-health outcomes given the available health system capacity. Efforts to achieve this are often framed through the lens of "health benefits packages" (HBPs), which seek to establish which services the public healthcare system should include in its provision. Analytic approaches widely used to weigh evidence in support of different interventions and inform the broader HBP deliberative process however have limitations. In this work, we propose the individual-based Thanzi La Onse (TLO) model as a uniquely-tailored tool to assist in the evaluation of Malawi-specific HBPs while addressing these limitations. By mechanistically modelling-and calibrating to extensive, country-specific data-the incidence of disease, health-seeking behaviour, and the capacity of the healthcare system to meet the demand for care under realistic constraints on human resources for health available, we were able to simulate the health gains achievable under a number of plausible HBP strategies for the country. We found that the HBP emerging from a linear constrained optimisation analysis (LCOA) achieved the largest health gain-∼8% reduction in disability adjusted life years (DALYs) between 2023 and 2042 compared to the benchmark scenario-by concentrating resources on high-impact treatments. This HBP however incurred a relative excess in DALYs in the first few years of its implementation. Other feasible approaches to prioritisation were assessed, including service prioritisation based on patient characteristics, rather than service type. Unlike the LCOA-based HBP, this approach achieved consistent health gains relative to the benchmark scenario on a year- to-year basis, and a 5% reduction in DALYs over the whole period, which suggests an approach based upon patient characteristics might prove beneficial in the future.

Health workforce needs in Malawi: analysis of the Thanzi La Onse integrated epidemiological model of care.

BACKGROUND: To make the best use of health resources, it is crucial to understand the healthcare needs of a population-including how needs will evolve and respond to changing epidemiological context and patient behaviour-and how this compares to the capabilities to deliver healthcare with the existing workforce. Existing approaches to planning either rely on using observed healthcare demand from a fixed historical period or using models to estimate healthcare needs within a narrow domain (e.g., a specific disease area or health programme). A new data-grounded modelling method is proposed by which healthcare needs and the capabilities of the healthcare workforce can be compared and analysed under a range of scenarios: in particular, when there is much greater propensity for healthcare seeking. METHODS: A model representation of the healthcare workforce, one that formalises how the time of the different cadres is drawn into the provision of units of healthcare, was integrated with an individual-based epidemiological model-the Thanzi La Onse model-that represents mechanistically the development of disease and ill-health and patients' healthcare seeking behaviour. The model was applied in Malawi using routinely available data and the estimates of the volume of health service delivered were tested against officially recorded data. Model estimates of the "time needed" and "time available" for each cadre were compared under different assumptions for whether vacant (or established) posts are filled and healthcare seeking behaviour. RESULTS: The model estimates of volume of each type of service delivered were in good agreement with the available data. The "time needed" for the healthcare workforce greatly exceeded the "time available" (overall by 1.82-fold), especially for pharmacists (6.37-fold) and clinicians (2.83-fold). This discrepancy would be largely mitigated if all vacant posts were filled, but the large discrepancy would remain for pharmacists (2.49-fold). However, if all of those becoming ill did seek care immediately, the "time needed" would increase dramatically and exceed "time supply" (2.11-fold for nurses and midwives, 5.60-fold for clinicians, 9.98-fold for pharmacists) even when there were no vacant positions. CONCLUSIONS: The results suggest that services are being delivered in less time on average than they should be, or that healthcare workers are working more time than contracted, or a combination of the two. Moreover, the analysis shows that the healthcare system could become overwhelmed if patients were more likely to seek care. It is not yet known what the health consequences of such changes would be but this new model provides-for the first time-a means to examine such questions.

The changes in health service utilisation in Malawi during the COVID-19 pandemic.

INTRODUCTION: The COVID-19 pandemic and the restriction policies implemented by the Government of Malawi may have disrupted routine health service utilisation. We aimed to find evidence for such disruptions and quantify any changes by service type and level of health care. METHODS: We extracted nationwide routine health service usage data for 2015-2021 from the electronic health information management systems in Malawi. Two datasets were prepared: unadjusted and adjusted; for the latter, unreported monthly data entries for a facility were filled in through systematic rules based on reported mean values of that facility or facility type and considering both reporting rates and comparability with published data. Using statistical descriptive methods, we first described the patterns of service utilisation in pre-pandemic years (2015-2019). We then tested for evidence of departures from this routine pattern, i.e., service volume delivered being below recent average by more than two standard deviations was viewed as a substantial reduction, and calculated the cumulative net differences of service volume during the pandemic period (2020-2021), in aggregate and within each specific facility. RESULTS: Evidence of disruptions were found: from April 2020 to December 2021, services delivered of several types were reduced across primary and secondary levels of care-including inpatient care (-20.03% less total interactions in that period compared to the recent average), immunisation (-17.61%), malnutrition treatment (-34.5%), accidents and emergency services (-16.03%), HIV (human immunodeficiency viruses) tests (-27.34%), antiretroviral therapy (ART) initiations for adults (-33.52%), and ART treatment for paediatrics (-41.32%). Reductions of service volume were greatest in the first wave of the pandemic during April-August 2020, and whereas some service types rebounded quickly (e.g., outpatient visits from -17.7% to +3.23%), many others persisted at lower level through 2021 (e.g., under-five malnutrition treatment from -15.24% to -42.23%). The total reduced service volume between April 2020 and December 2021 was 8 066 956 (-10.23%), equating to 444 units per 1000 persons. CONCLUSION: We have found substantial evidence for reductions in health service delivered in Malawi during the COVID-19 pandemic which may have potential health consequences, the effect of which should inform how decisions are taken in the future to maximise the resilience of healthcare system during similar events.

Estimating the health burden of road traffic injuries in Malawi using an individual-based model.

BACKGROUND: Road traffic injuries are a significant cause of death and disability globally. However, in some countries the exact health burden caused by road traffic injuries is unknown. In Malawi, there is no central reporting mechanism for road traffic injuries and so the exact extent of the health burden caused by road traffic injuries is hard to determine. A limited number of models predict the incidence of mortality due to road traffic injury in Malawi. These estimates vary greatly, owing to differences in assumptions, and so the health burden caused on the population by road traffic injuries remains unclear. METHODS: We use an individual-based model and combine an epidemiological model of road traffic injuries with a health seeking behaviour and health system model. We provide a detailed representation of road traffic injuries in Malawi, from the onset of the injury through to the final health outcome. We also investigate the effects of an assumption made by other models that multiple injuries do not contribute to health burden caused by road accidents. RESULTS: Our model estimates an overall average incidence of mortality between 23.5 and 29.8 per 100,000 person years due to road traffic injuries and an average of 180,000 to 225,000 disability-adjusted life years (DALYs) per year between 2010 and 2020 in an estimated average population size of 1,364,000 over the 10-year period. Our estimated incidence of mortality falls within the range of other estimates currently available for Malawi, whereas our estimated number of DALYs is greater than the only other estimate available for Malawi, the GBD estimate predicting and average of 126,200 DALYs per year over the same time period. Our estimates, which account for multiple injuries, predict a 22-58% increase in overall health burden compared to the model ran as a single injury model. CONCLUSIONS: Road traffic injuries are difficult to model with conventional modelling methods, owing to the numerous types of injuries that occur. Using an individual-based model framework, we can provide a detailed representation of road traffic injuries. Our results indicate a higher health burden caused by road traffic injuries than previously estimated.